Wei Huang

According to our database, Wei Huang authored at least 19 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLM.

Hanrong Ye, Chao-Han Huck Yang, Arushi Goel, Wei Huang, Ligeng Zhu, Yuanhang Su, Sean Lin, An-Chieh Cheng, Zhen Wan, Jinchuan Tian, Yuming Lou, Dong Yang, Zhijian Liu, Yukang Chen, Ambrish Dantrey, Ehsan Jahangiri, Sreyan Ghosh, Daguang Xu, Ehsan Hosseini-Asl, Danial Mohseni-Taheri, Vidya Murali, Sifei Liu, Yao Lu, Oluwatobi Olabiyi, Yu-Chiang Frank Wang, Rafael Valle, Bryan Catanzaro, Andrew Tao, Song Han, Jan Kautz, Hongxu Yin, Pavlo Molchanov

CoRR, October, 2025

QeRL: Beyond Efficiency - Quantization-enhanced Reinforcement Learning for LLMs.

Wei Huang, Yi Ge, Shuai Yang, Yicheng Xiao, Huizi Mao, Yujun Lin, Hanrong Ye, Sifei Liu, Ka Chun Cheung, Hongxu Yin, Yao Lu, Xiaojuan Qi, Song Han, Yukang Chen

CoRR, October, 2025

MC#: Mixture Compressor for Mixture-of-Experts Large Models.

Wei Huang, Yue Liao, Yukang Chen, Jianhui Liu, Haoru Tan, Si Liu, Shiming Zhang, Shuicheng Yan, Xiaojuan Qi

CoRR, October, 2025

LongLive: Real-time Interactive Long Video Generation.

Shuai Yang, Wei Huang, Ruihang Chu, Yicheng Xiao, Yuyang Zhao, Xianbang Wang, Muyang Li, Enze Xie, Yingcong Chen, Yao Lu, Song Han, Yukang Chen

CoRR, September, 2025

Scaling RL to Long Videos.

Yukang Chen, Wei Huang, Baifeng Shi, Qinghao Hu, Hanrong Ye, Ligeng Zhu, Zhijian Liu, Pavlo Molchanov, Jan Kautz, Xiaojuan Qi, Sifei Liu, Hongxu Yin, Yao Lu, Song Han

CoRR, July, 2025

DBellQuant: Breaking the Bell with Double-Bell Transformation for LLMs Post Training Binarization.

Zijian Ye, Wei Huang, Yifei Yu, Tianhe Ren, Zhongrui Wang, Xiaojuan Qi

CoRR, July, 2025

MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO.

Yicheng Xiao, Lin Song, Yukang Chen, Yingmin Luo, Yuxin Chen, Yukang Gan, Wei Huang, Xiu Li, Xiaojuan Qi, Ying Shan

CoRR, May, 2025

SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models.

Wei Huang, Haotong Qin, Yangdong Liu, Yawei Li, Qinshuo Liu, Xianglong Liu, Luca Benini, Michele Magno, Shiming Zhang, Xiaojuan Qi

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Data Pruning by Information Maximization.

Haoru Tan, Sitong Wu, Wei Huang, Shizhen Zhao, Xiaojuan Qi

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Mixture Compressor for Mixture-of-Experts LLMs Gains More.

Wei Huang, Yue Liao, Jianhui Liu, Ruifei He, Haoru Tan, Shiming Zhang, Hongsheng Li, Si Liu, Xiaojuan Qi

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection.

Songhao Han, Wei Huang, Hairong Shi, Le Zhuo, Xiu Su, Shifeng Zhang, Xu Zhou, Xiaojuan Qi, Yue Liao, Si Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

An empirical study of LLaMA3 quantization: from LLMs to MLLMs.

Wei Huang, Xingyu Zheng, Xudong Ma, Haotong Qin, Chengtao Lv, Hong Chen, Jie Luo, Xiaojuan Qi, Xianglong Liu, Michele Magno

Vis. Intell., 2024

MC-MoE: Mixture Compressor for Mixture-of-Experts LLMs Gains More.

Wei Huang, Yue Liao, Jianhui Liu, Ruifei He, Haoru Tan, Shiming Zhang, Hongsheng Li, Si Liu, Xiaojuan Qi

CoRR, 2024

SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models.

Wei Huang, Haotong Qin, Yangdong Liu, Yawei Li, Xianglong Liu, Luca Benini, Michele Magno, Xiaojuan Qi

CoRR, 2024

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study.

Wei Huang, Xudong Ma, Haotong Qin, Xingyu Zheng, Chengtao Lv, Hong Chen, Jie Luo, Xiaojuan Qi, Xianglong Liu, Michele Magno

CoRR, 2024

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs.

Wei Huang, Yangdong Liu, Haotong Qin, Ying Li, Shiming Zhang, Xianglong Liu, Michele Magno, Xiaojuan Qi

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SNNGX: Securing Spiking Neural Networks with Genetic XOR Encryption on RRAM-based Neuromorphic Accelerator.

Kwunhang Wong, Songqi Wang, Wei Huang, Xinyuan Zhang, Yangu He, Karl Ming Him Lai, Yuzhong Jiao, Ning Lin, Xiaojuan Qi, Xiaoming Chen, Zhongrui Wang

Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, 2024

2023

OHQ: On-chip Hardware-aware Quantization.

Wei Huang, Haotong Qin, Yangdong Liu, Jingzhuo Liang, Yifu Ding, Ying Li, Xianglong Liu

CoRR, 2023

An innovative experimental teaching method of hardware-software co-design-Taking a hardware accelerator of neural network using FPGA.

Ying Li, Jingzhuo Liang, Gui Shi Jie, Yangdong Liu, Wei Huang, Yue Yan, Xianglong Liu

Proceedings of the IEEE Frontiers in Education Conference, 2023